PhD - Statistics
Applications are welcomed for students wishing to undertake a PhD in Statistics at the University of St Andrews. Full funding (fees, plus stipend of approx. £15,600) is available for well-qualified students; we encourage applications as soon as possible to maximize your chances of being funded. UK, EU and other overseas students are all encouraged to apply. New PhD students would typically start in September 2021, but this is flexible.
Members of the Statistics Division at St Andrews are particularly active in the fields of statistical ecology, and in statistical medicine and molecular biology. Other research areas include Bayesian statistical inference, computer-intensive inference, data mining, data smoothing, latent state models and experimental design.
General applications from potential students interested in these areas are welcome. In addition, we are looking for candidates for the following specific projects; more details of these, the PhD environment and the application process are at the following web site:
https://tinyurl.com/StAndStatsPhD2021 (pdf document; full address https://www.st-andrews.ac.uk/assets/university/schools/school-of-mathematics-and-statistics/documents/st-andrews-statistics-phd-opportunities-2021-2022.pdf).
Specific projects (supervisor in brackets):
- Design of experiments (Rosemary Bailey)
- Statistical models for digital ecological surveys (David Borchers)
- Modelling encounters in surveys of unmarked animal populations (David Borchers and Richard Glennie)
- Object classification from mobile and static sensor feeds (Carl Donovan)
- Trading in peer-to-peer (P2P) markets (Carl Donovan)
- Automated evaluation of geo-political risk (Carl Donovan)
- Investigating modes of action of genetic risk variants through integrated analysis of multiple high-dimensional “omics” data (Andy Lynch and Michail Papathomas)
- Statistical inference for stochastic dynamical systems in biology (Giorgos Minas and Jochen Kursawe)
- Strategies for detecting high probability dependence structures (Michail Papathomas)
- Bayesian identifiability for log-linear models (Michail Papathomas)
- Modelling local population dynamics for whale sharks in the Maldives (Hannah Worthington)
For informal discussion about any aspect of the above, contact Prof. Len Thomas <firstname.lastname@example.org>.